Abstract: The harsh natural environment in plateau area brings severe challenges to the normal operation of air defense early-warning radar. In order to improve the efficiency of radar in plateau area and reduce the maintenance cost, the reasonable environmental adaptability assessment should be taken for the air defense early-warning radar in the development stage. In view of the above requirements, a self-learning fuzzy grey method is proposed. A self-learning model based on Bayesian estimation about index weight is established to realize the adaptive adjustment of subjective and objective weight preference coefficients in the combination weighting method by analying the key factors affecting the plateau environmental adaptability of air defense early-warning radar. For the fuzzy relationship among evaluation index factors and evaluation states, the membership function is constructed from the radar failure rates under the influence of various environmental indexes to realize the assignment of valuation index under uncertainty conditions. On the basis of the above work, a self-learning fuzzy grey model for plateau environmental adaptability assessment of air defense early-warning radar is built, in which the influence of information grey value is considered. A simulation experiment of evaluating the plateau environmental adaptability with and without learning process was conducted on various systems and components of an air defense early-warning radar. The results show that the proposed method not only fully considers the subjective experience of experts, but also follows the data law presented by objective facts, which makes the evaluation results more reasonable.

Key words: airdefenseearly-warningradar, plateauenvironmentadaptabilityassessment, self-learningmodel, fuzzygreydegree, membershipfunction